As the interest in utilizing AI/machine learning in healthcare continues to grow, healthcare systems are adopting algorithms to enhance patient care, alleviate clinician burnout, and improve operational efficiency. However, while these applications may appear promising, they also carry certain risks, including the potential to automate and reinforce existing health disparities.
During this seminar, we will introduce the ABCDS Oversight framework developed at Duke Health. This comprehensive framework focuses on the governance, evaluation, and monitoring of clinical algorithms, providing participants with practical guidance to ensure the responsible implementation of AI/ML. Specifically, we will highlight how high-level principles can be translated into actionable steps for developers, allowing them to maximize patient benefit while minimizing potential risks.
Additionally, we will provide participants with our Bias Analysis and Mitigation template, a valuable tool for identifying and addressing potential sources of bias in AI/ML algorithms. This template facilitates the anticipation of associated harms and guides the implementation of strategies to mitigate or prevent biases. By utilizing this tool, developers can proactively address bias concerns and work towards equitable healthcare outcomes.
We will also address the challenges posed by large language models (LLMs) powered by generative AI, such as ChatGPT. While LLMs have the ability to generate text, their outputs must be carefully monitored and controlled to avoid unintended biases or misinformation. We will explore considerations and strategies necessary for effectively evaluating and governing LLMs within the healthcare context.
Lastly, we will discuss the competencies needed for educators working to prepare the next generation of health professionals. Universities can play a crucial role in supporting healthcare professionals to build critical competencies in AI/ML by strengthening curricula and providing opportunities for continuing professional development.
Whether you are a developer, a healthcare professional, or simply an enthusiast in the field of AI/ML, this seminar will offer valuable insights and practical tools for promoting responsible and equitable implementation of AI/ML in healthcare settings. Join us to learn how you can contribute to shaping the future of healthcare delivery through AI/ML innovation, educating next-generation health professionals, and ensuring the best possible outcomes for patients at Duke and beyond.
Presenter Bios
(ABCDS) Oversight program. She provides operational support and peer review for clinical decision support software proposed for use within the Duke University Health System (DUHS). Before joining Duke, she worked as a data scientist at UNC Health, where she led a project responsible for building, evaluating, and implementing clinical risk models in the electronic health records (EHR). Sophia also brings experience in research, project coordination, and care delivery from her early career spent in HIV prevention and treatment services. She holds Master’s degrees in Analytics and Public Health from NC State University and the University of Copenhagen and has more than 10 years of experience working at the intersection of data science, equity, and public health.Dr. Cary is an Associate Professor and Elizabeth C. Clipp Term Chair of Nursing in the Duke University
School of Nursing. Dually trained as a health services researcher and applied data scientist, Dr. Cary uses AI and machine learning to study health disparities related to aging and develop strategies to advance health equity and improve healthcare delivery to older adults in diverse populations. His research has been supported by the National Library of Medicine, National Institute of Nursing Research, and the Duke Clinical and Translational Science Institute. He has published more than 50 manuscripts, book chapters, and editorials and has mentored numerous students and faculty members. In 2022, he was inducted as a Fellow of the American Academy of Nursing for his significant contributions to improve health and healthcare.
Most recently, he was selected by Duke Health to be the inaugural AI Health Equity Scholar. In this health system leadership position, he leads an interdisciplinary team in identifying clinical algorithms that perpetuate racial and ethnic health and health care disparities and implementing system-wide standards for mitigating their harmful discriminatory effects on patients. These meaningful contributions are vital to addressing health disparities and promoting equitable health outcomes for all patients at Duke and beyond.
Dr. Cary received a bachelor’s degree in health services administration from James Madison University. He also earned a bachelors, masters, and doctoral degree in nursing from the University of Virginia.